The stance detection task has been defined in previous work as consisting in determining the viewpoint of an utterance with respect to a target topic [1]}, while others define it as that consisting in determining an author's viewpoint with respect to the veracity of a rumour, usually referred to as rumour stance classification [2]}. SardiStance focuses on the former, and is split into two subtasks: Textual Stance Detection (Task A) and Contextual Stance Detection (Task B) [3]}. Baselines are provided for Task A using SVM+unigrams as (f-avg. \(0.578\) ), and for Task B as (f-avg. \(0.628\) ) [4]}.
